Raedan AI

The Hidden Value of Unstructured Data

The Hidden Value of Unstructured Data

What will you do today to leverage Cognitive AI for your organisation? Put your business on the path too advanced Artificial Intelligence technology.

More than 60% of global data and analytics decision-makers say that their company is sitting on 100 or more terabytes of data.1 Customer and transaction data, product information, market intelligence, email and social media content make up just some of the 2.5 quintillion bytes of data that is being created on a daily basis.2 In other words, businesses are producing the text equivalent of a new Library of Congress every day.

The question is, how much of this information is being utilized to help your business?

The reality is that the vast majority of enterprise data is actually unavailable to business intelligence, operations and analytics processes for one simple reason: it is unstructured.

The very nature of this information, and the abundance of it, makes it difficult to manage yet extremely valuable for decision making. It’s time for more organizations to take advantage of the greatest source of available information: their own unstructured data.

A large portion of internal or external content that organizations rely on to do business—news feeds, web content, emails, presentations, customer feedback, market reports, compliance documentation—is classified as unstructured data, which makes up more than 80% of enterprise information.3

Effective Enterprises use all data

Businesses that understand this are not waiting until 2020. They know that the volume and quantity of their data is simply impossible to manage using traditional methods. They understand that a smart technical solution is required to extract business value from all of their data, especially unstructured information, so that they can quickly and reliably make sense of it.

This requirement is not suited for just any technology. Instead, it’s a task for systems that can read and comprehend human language and information in a way that is dynamic, scalable and, most importantly, intelligent.

To understand why, it’s necessary to look at how data is typically processed.

IDC predicts that within a year, organizations that analyze relevant data—both structured and unstructured data—and deliver actionable information to decision makers will achieve an extra $430 billion in productivity gains over competitors that do not perform such analysis.4

What makes unstructured information so challenging?

It’s important to understand that not all data is the same. Structured data is most often located in cells in a database, and usually deals with a clear, predetermined business purpose. Instead, unstructured data is most everything else. The most complex portion of unstructured information is textual—social media data, news feeds, transcripts, documents, etc. It can’t be easily organized into a database, and it can be ambiguous and difficult to manage because it is characterized by an important trait: human language.

Unstructured data is the opposite of structured data: everyday language can contain endless amounts and types of information, is expressed in many different ways, and meaning depends significantly on context. For example, consider that the 500 most common words in everyday language have an average of 23 different meanings. This means that even a simple sentence of just 10 words could have a huge number of different meanings.

This is what makes processing unstructured information so difficult. If we want a machine to understand our language, we have to go beyond the logic of the numeric calculation typically associated with software.

This is why natural language-based (or concept) classification and extraction technologies make the difference. They try to replicate the process humans follow when they read and understand the meanings of words in context.

Instead, traditional technologies that are designed to deal with numbers process words in the only way they can: by pretending they are numbers. In doing so, they “see” words but do not understand meanings. They can “match” two or more words as appearing together but cannot determine what they mean.

The business value of understanding meaning:

As basic, mostly keyword-extraction-based technology becomes outdated and less effective, improved complex concept extractions will dictate which providers lead the pack. Vendors that can provide these advanced features position themselves to successfully deliver enterprise-grade text analytics solutions to their customers.

(The Forrester Wave™: AIBased Text Analytics Platforms, Q2 2018).5

The challenge of deploying a seamless solution that makes sense of unstructured information and merges it with structured data to exploit the value of all data is therefore no longer optional, but a requirement for enterprises.

Despite the complexities of handling human language and the meaning of texts, it’s a necessary process if you want to capture the full value of your information. For one, effectively managing unstructured information enables businesses to take advantage of all the knowledge available. Whether this information is standalone or integrated with the more familiar structured data, it is a critical success factor in decision making.

Effectively processing natural language and, in a broader sense, being able to accurately “make sense” of unstructured data at scale can generate exponential business value, accelerating knowledge discovery, and ensuring delivery of the right information at the right time, as well as empowering process automation by adding intelligence into Robotic Process Automation.

In fact, the capability of understanding “knowledge,” whether in the form of documents, emails, research output, regulatory and compliance reports, news feeds or tweets, can radically change the way knowledge is discovered. At the same time, in the rush to take advantage of innovative technologies like robotic process automation (RPA), the need for text analytics and natural language understanding is often forgotten. Instead, information-intensive processes such as customer interaction, invoice data extraction and classification, claims management and contracts verification can be fully and intelligently automated only through the accurate comprehension of unstructured data.

Artificial Intelligence: Enabling human comprehension and insight at scale

Organizations can now understand the meaning of words in context by deploying a high-performance Artificial intelligence (AI) technology with features built for processing large quantities of text with the highest levels of precision.

Cogito (Latin for ‘I think’) is the Expert System cognitive artificial intelligence platform that enables organizations to understand data, and empowers them to take control of their decision-making processes.

By enabling human-like comprehension, Cogito adds context to content, turning information into knowledge and supporting organizations to extend automation to processes that require understanding the content of complex documents such as insurance claims, financial services, risk management reports, underwriting documents or engineering surveys, etc.

  • Obtain effective and real-time insight on strategic initiatives, partners and any third parties
  • Mitigate and even completely avoid risks for operations, reputation, etc. through information analysis and monitoring
  • Know what competitors are doing and intercept market trends
  • Implement automation for the broader, more complex set of processes that involve data
  • Free up teams to focus on more creative or critical activities inside the organization

Cognitive Artificial Intelligence helps businesses make better, faster and cheaper decisions. Organizations must be willing to work with the machine, and not treat it as a servant or expect it to be a fully automated process with no human intervention. Machines formulate based on human input.

How will you use Artificial Intelligence for your business?

As companies increasingly recognize the business implications and actionable benefits of AI, the question becomes: How will you use AI for your business?

Thanks to the Cogito platform based on AI algorithms, organizations can effectively support and improve unstructured information management and text analytics in order to:

  • Leverage all information, combining internal knowledge with other information sources to extract relevant data
  • Provide effective and real-time insight on strategic initiatives, partners and any third parties
  • Mitigate and even completely avoid risks for operations, reputation, etc. through information analysis and monitoring
  • Know what competitors are doing and intercept market trends
  • Implement automation for the broader, more complex set of processes that involve data
  • Free up teams to focus on more creative or critical activities inside the organization
  • See the entire business though a different perspective

End Notes
  1. https://www.forrester.com/report/The+Forrester+Wave+AIBased+Text+Analytics+Platforms+Q2+2018/-/E-RES141340#
  2. https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/#2159d46060ba
  3. https://www.forbes.com/sites/forbestechcouncil/2017/06/05/the-big-unstructured-data-problem/#1d60a9a1493a
  4. https://www.idc.com/promo/thirdplatform/digitaltransformation/information
  5. https://www.forrester.com/report/The+Forrester+Wave+AIBased+Text+Analytics+Platforms+Q2+2018/-/E-RES141340#